Instructions to use jax-diffusers-event/canny-coyo1m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jax-diffusers-event/canny-coyo1m with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("jax-diffusers-event/canny-coyo1m") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 709f1b671f3eadbe56d66f2a21bf73c7d83b4aab3cda4acf7a1dc73aeab72ca5
- Size of remote file:
- 4.93 MB
- SHA256:
- 85792c275b283d636c01812f5b0ca89a83958db39ee592b04fb9c8ec6479f670
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